Towards rainfall interception capacity estimation using ALS LiDAR data - Publication - Bridge of Knowledge

Search

Towards rainfall interception capacity estimation using ALS LiDAR data

Abstract

In this study we develop a spatial model for interception capacity of vegetation based on LiDAR data. The study is conducted in the natural wetland river valley dominated meadows, reeds and small bushes. The multiple regression model was chosen to relate the field measurements of interception capacity and LiDAR statistics at 2m grid. The optimal model was chosen by stepwise selection and further manual variables selection resulting in the r2 of 0.52 and the residual standard error of 0.27 mm. The model preserved the vegetation pattern spatially and showed reasonable estimates for both vegetation covered and not covered by field sampling. The model was, however, affected by LiDAR measurements corrupted by river inundation. The results show good perspective for using LiDAR data for interception capacity estimation.

Citations

  • 6

    CrossRef

  • 0

    Web of Science

  • 6

    Scopus

Authors (4)

Cite as

Full text

full text is not available in portal

Keywords

Details

Category:
Conference activity
Type:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Title of issue:
Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International strony 735 - 738
Language:
English
Publication year:
2015
Bibliographic description:
Berezowski T., Chormanski J., Kleniewska M., Szporak-Wasilewska S.: Towards rainfall interception capacity estimation using ALS LiDAR data// Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International/ : , 2015, s.735-738
DOI:
Digital Object Identifier (open in new tab) 10.1109/igarss.2015.7325869
Verified by:
Gdańsk University of Technology

seen 129 times

Recommended for you

Meta Tags